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The Analysis of Survey Data Using the Bootstrap

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Contributions to Sampling Statistics

Part of the book series: Contributions to Statistics ((CONTRIB.STAT.))

Abstract

We first review bootstrap variance estimation for estimators of finite population quantities such as population totals or means. In this context, the bootstrap is typically implemented by producing a set of bootstrap design weights that account for the variability due to sample selection. Sometimes, survey analysts are interested in making inferences about model parameters. We then describe how to modify bootstrap design weights so as to account for the variability resulting from the analyst’s model. Finally, we discuss bootstrap tests of hypotheses for survey data.

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Acknowledgments

I would like to thank the reviewer for the constructive comments that helped improve the overall quality of the paper.

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Authors and Affiliations

  1. Statistical Research and Innovation Division, Statistics Canada, Ottawa, ON, Canada

    Jean-François Beaumont

Authors
  1. Jean-François Beaumont
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Correspondence to Jean-François Beaumont .

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Editors and Affiliations

  1. Dept. of Sociology and Social Research, University of Milano-Bicocca, Milano, Milano, Italy

    Fulvia Mecatti

  2. Dept. of Statistical Sciences, Sapienza - University of Rome, Roma, Roma, Italy

    Pier Luigi Conti

  3. Dept. Economics, Finance and Statistics, University of Perugia, Perugia, Perugia, Italy

    Maria Giovanna Ranalli

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Beaumont, JF. (2014). The Analysis of Survey Data Using the Bootstrap. In: Mecatti, F., Conti, P., Ranalli, M. (eds) Contributions to Sampling Statistics. Contributions to Statistics. Springer, Cham. https://doi.org/10.1007/978-3-319-05320-2_4

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